Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	546
Missing cells	546
Missing cells (%)	7.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	59.8 KiB
Average record size in memory	112.2 B

Variable types

Numeric	8
Categorical	5
Unsupported	1

Warnings

`is_failed` has constant value "1"	Constant
`customer_id` has a high cardinality: 438 distinct values	High cardinality
`order_date` has a high cardinality: 320 distinct values	High cardinality
`transmission_id` is highly correlated with `is_failed`	High correlation
`is_failed` is highly correlated with `transmission_id` and 1 other fields	High correlation
`payment_id` is highly correlated with `is_failed`	High correlation
`customer_order_rank` has 546 (100.0%) missing values	Missing
`customer_id` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`customer_order_rank` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`order_hour` has 7 (1.3%) zeros	Zeros
`voucher_amount` has 520 (95.2%) zeros	Zeros
`delivery_fee` has 417 (76.4%) zeros	Zeros

Reproduction

Analysis started	2021-02-25 23:04:57.437821
Analysis finished	2021-02-25 23:05:05.667077
Duration	8.23 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

df_index
Real number (ℝ_≥0)

UNIQUE

Distinct	546
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	413462.0824
Minimum	2699
Maximum	786062
Zeros	0
Zeros (%)	0.0%
Memory size	4.4 KiB

Quantile statistics

Minimum	2699
5-th percentile	47132.25
Q1	236975
median	388468.5
Q3	615865.25
95-th percentile	757699.75
Maximum	786062
Range	783363
Interquartile range (IQR)	378890.25

Descriptive statistics

Standard deviation	227584.7071
Coefficient of variation (CV)	0.5504367069
Kurtosis	-1.162275483
Mean	413462.0824
Median Absolute Deviation (MAD)	186137
Skewness	-0.02591198913
Sum	225750297
Variance	5.179479889 × 10¹⁰
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
146432	1	0.2%
431756	1	0.2%
238214	1	0.2%
142983	1	0.2%
729736	1	0.2%
351881	1	0.2%
431754	1	0.2%
2699	1	0.2%
586596	1	0.2%
232158	1	0.2%
Other values (536)	536	98.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2699	1	0.2%
3667	1	0.2%
4197	1	0.2%
4835	1	0.2%
6315	1	0.2%

Value	Count	Frequency (%)
786062	1	0.2%
785818	1	0.2%
782962	1	0.2%
782393	1	0.2%
781461	1	0.2%

customer_id
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	438
Distinct (%)	80.2%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

787f67dc55ca	10
415e22e514c0	5
d956116d863d	5
52ecbd9f90cf	5
59c241c6aa7c	4
Other values (433)	517

Length

Max length	12
Median length	12
Mean length	12
Min length	12

Characters and Unicode

Total characters	6552
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	370 ?
Unique (%)	67.8%

Sample

1st row	00c9c435cd4a
2nd row	010a7ac13c41
3rd row	0132d2b7563c
4th row	0173219940e8
5th row	01e4f035a965

Value	Count	Frequency (%)
787f67dc55ca	10	1.8%
415e22e514c0	5	0.9%
d956116d863d	5	0.9%
52ecbd9f90cf	5	0.9%
59c241c6aa7c	4	0.7%
71d6e4771116	4	0.7%
edcae608c263	4	0.7%
69ace890f21f	4	0.7%
3b69f4464d7a	4	0.7%
525aec76634e	4	0.7%
Other values (428)	497	91.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
787f67dc55ca	10	1.8%
415e22e514c0	5	0.9%
d956116d863d	5	0.9%
52ecbd9f90cf	5	0.9%
59c241c6aa7c	4	0.7%
71d6e4771116	4	0.7%
edcae608c263	4	0.7%
69ace890f21f	4	0.7%
3b69f4464d7a	4	0.7%
525aec76634e	4	0.7%
Other values (428)	497	91.0%

Most occurring characters

Value	Count	Frequency (%)
7	458	7.0%
5	442	6.7%
e	442	6.7%
1	433	6.6%
c	428	6.5%
f	428	6.5%
6	426	6.5%
9	400	6.1%
4	400	6.1%
b	400	6.1%
Other values (6)	2295	35.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4058	61.9%
Lowercase Letter	2494	38.1%

Most frequent character per category

Value	Count	Frequency (%)
7	458	11.3%
5	442	10.9%
1	433	10.7%
6	426	10.5%
9	400	9.9%
4	400	9.9%
8	387	9.5%
3	375	9.2%
0	373	9.2%
2	364	9.0%

Value	Count	Frequency (%)
e	442	17.7%
c	428	17.2%
f	428	17.2%
b	400	16.0%
d	399	16.0%
a	397	15.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	4058	61.9%
Latin	2494	38.1%

Most frequent character per script

Value	Count	Frequency (%)
7	458	11.3%
5	442	10.9%
1	433	10.7%
6	426	10.5%
9	400	9.9%
4	400	9.9%
8	387	9.5%
3	375	9.2%
0	373	9.2%
2	364	9.0%

Value	Count	Frequency (%)
e	442	17.7%
c	428	17.2%
f	428	17.2%
b	400	16.0%
d	399	16.0%
a	397	15.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6552	100.0%

Most frequent character per block

Value	Count	Frequency (%)
7	458	7.0%
5	442	6.7%
e	442	6.7%
1	433	6.6%
c	428	6.5%
f	428	6.5%
6	426	6.5%
9	400	6.1%
4	400	6.1%
b	400	6.1%
Other values (6)	2295	35.0%

order_date
Categorical

HIGH CARDINALITY

Distinct	320
Distinct (%)	58.6%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

2016-11-13	12
2016-07-17	9
2016-07-31	8
2016-08-06	8
2015-10-10	7
Other values (315)	502

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	5460
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	197 ?
Unique (%)	36.1%

Sample

1st row	2017-01-21
2nd row	2016-06-17
3rd row	2016-10-12
4th row	2015-09-03
5th row	2017-02-23

Value	Count	Frequency (%)
2016-11-13	12	2.2%
2016-07-17	9	1.6%
2016-07-31	8	1.5%
2016-08-06	8	1.5%
2015-10-10	7	1.3%
2016-07-11	6	1.1%
2016-07-06	6	1.1%
2016-07-10	6	1.1%
2016-02-16	5	0.9%
2016-03-20	5	0.9%
Other values (310)	474	86.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
2016-11-13	12	2.2%
2016-07-17	9	1.6%
2016-07-31	8	1.5%
2016-08-06	8	1.5%
2015-10-10	7	1.3%
2016-07-11	6	1.1%
2016-07-06	6	1.1%
2016-07-10	6	1.1%
2016-02-16	5	0.9%
2016-03-20	5	0.9%
Other values (310)	474	86.8%

Most occurring characters

Value	Count	Frequency (%)
0	1195	21.9%
-	1092	20.0%
1	1058	19.4%
2	868	15.9%
6	467	8.6%
5	208	3.8%
7	192	3.5%
3	114	2.1%
8	95	1.7%
9	94	1.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4368	80.0%
Dash Punctuation	1092	20.0%

Most frequent character per category

Value	Count	Frequency (%)
0	1195	27.4%
1	1058	24.2%
2	868	19.9%
6	467	10.7%
5	208	4.8%
7	192	4.4%
3	114	2.6%
8	95	2.2%
9	94	2.2%
4	77	1.8%

Value	Count	Frequency (%)
-	1092	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5460	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	1195	21.9%
-	1092	20.0%
1	1058	19.4%
2	868	15.9%
6	467	8.6%
5	208	3.8%
7	192	3.5%
3	114	2.1%
8	95	1.7%
9	94	1.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5460	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	1195	21.9%
-	1092	20.0%
1	1058	19.4%
2	868	15.9%
6	467	8.6%
5	208	3.8%
7	192	3.5%
3	114	2.1%
8	95	1.7%
9	94	1.7%

order_hour
Real number (ℝ_≥0)

ZEROS

Distinct	21
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	17.21611722
Minimum	0
Maximum	23
Zeros	7
Zeros (%)	1.3%
Memory size	4.4 KiB

Quantile statistics

Minimum	0
5-th percentile	10
Q1	15
median	18
Q3	20
95-th percentile	22
Maximum	23
Range	23
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	4.303721063
Coefficient of variation (CV)	0.2499820958
Kurtosis	3.641983137
Mean	17.21611722
Median Absolute Deviation (MAD)	2
Skewness	-1.64386451
Sum	9400
Variance	18.52201499
Monotocity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
20	81	14.8%
19	71	13.0%
18	70	12.8%
21	49	9.0%
17	48	8.8%
22	37	6.8%
14	32	5.9%
16	32	5.9%
13	26	4.8%
12	21	3.8%
Other values (11)	79	14.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	7	1.3%
1	1	0.2%
2	1	0.2%
3	8	1.5%
5	1	0.2%

Value	Count	Frequency (%)
23	17	3.1%
22	37	6.8%
21	49	9.0%
20	81	14.8%
19	71	13.0%

customer_order_rank
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	546
Missing (%)	100.0%
Memory size	4.4 KiB

is_failed
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

1	546

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	546
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Value	Count	Frequency (%)
1	546	100.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
1	546	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	546	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	546	100.0%

Most frequent character per category

Value	Count	Frequency (%)
1	546	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	546	100.0%

Most frequent character per script

Value	Count	Frequency (%)
1	546	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	546	100.0%

Most frequent character per block

Value	Count	Frequency (%)
1	546	100.0%

voucher_amount
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1096217949
Minimum	0
Maximum	5.145
Zeros	520
Zeros (%)	95.2%
Memory size	4.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	5.145
Range	5.145
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.5712117285
Coefficient of variation (CV)	5.210749643
Kurtosis	47.84982812
Mean	0.1096217949
Median Absolute Deviation (MAD)	0
Skewness	6.511343966
Sum	59.8535
Variance	0.3262828388
Monotocity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	520	95.2%
2.058	7	1.3%
1.029	6	1.1%
1.715	5	0.9%
5.145	4	0.7%
2.744	1	0.2%
3.43	1	0.2%
2.5725	1	0.2%
1.372	1	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	520	95.2%
1.029	6	1.1%
1.372	1	0.2%
1.715	5	0.9%
2.058	7	1.3%

Value	Count	Frequency (%)
5.145	4	0.7%
3.43	1	0.2%
2.744	1	0.2%
2.5725	1	0.2%
2.058	7	1.3%

delivery_fee
Real number (ℝ_≥0)

ZEROS

Distinct	19
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.2082970147
Minimum	0
Maximum	2.2185
Zeros	417
Zeros (%)	76.4%
Memory size	4.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1.4297
Maximum	2.2185
Range	2.2185
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4338700469
Coefficient of variation (CV)	2.082939343
Kurtosis	4.347234072
Mean	0.2082970147
Median Absolute Deviation (MAD)	0
Skewness	2.215072646
Sum	113.73017
Variance	0.1882432176
Monotocity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
0	417	76.4%
0.493	39	7.1%
0.986	23	4.2%
1.4297	16	2.9%
0.7395	14	2.6%
0.46835	10	1.8%
1.479	5	0.9%
1.2325	4	0.7%
0.2465	3	0.5%
1.7255	3	0.5%
Other values (9)	12	2.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	417	76.4%
0.2465	3	0.5%
0.3451	1	0.2%
0.46835	10	1.8%
0.493	39	7.1%

Value	Count	Frequency (%)
2.2185	1	0.2%
2.0706	2	0.4%
1.972	2	0.4%
1.7255	3	0.5%
1.479	5	0.9%

amount_paid
Real number (ℝ_≥0)

Distinct	270
Distinct (%)	49.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	10.75323626
Minimum	0
Maximum	237.5163
Zeros	2
Zeros (%)	0.4%
Memory size	4.4 KiB

Quantile statistics

Minimum	0
5-th percentile	4.24269
Q1	5.92596
median	8.349975
Q3	11.682
95-th percentile	20.709
Maximum	237.5163
Range	237.5163
Interquartile range (IQR)	5.75604

Descriptive statistics

Standard deviation	15.47884392
Coefficient of variation (CV)	1.439459112
Kurtosis	169.1626712
Mean	10.75323626
Median Absolute Deviation (MAD)	2.747925
Skewness	11.95427775
Sum	5871.267
Variance	239.5946092
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5.31	21	3.8%
6.372	11	2.0%
4.24269	10	1.8%
6.903	10	1.8%
7.434	8	1.5%
4.248	8	1.5%
9.027	8	1.5%
5.2569	7	1.3%
6.1065	7	1.3%
12.4785	7	1.3%
Other values (260)	449	82.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.4%
1.31688	1	0.2%
1.7523	1	0.2%
2.655	2	0.4%
2.69748	1	0.2%

Value	Count	Frequency (%)
237.5163	2	0.4%
77.6853	1	0.2%
62.6049	1	0.2%
57.348	1	0.2%
51.0822	1	0.2%

restaurant_id
Real number (ℝ_≥0)

Distinct	432
Distinct (%)	79.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	172961373.5
Minimum	233498
Maximum	332673498
Zeros	0
Zeros (%)	0.0%
Memory size	4.4 KiB

Quantile statistics

Minimum	233498
5-th percentile	32303498
Q1	85195998
median	183173498
Q3	252753498
95-th percentile	305593498
Maximum	332673498
Range	332440000
Interquartile range (IQR)	167557500

Descriptive statistics

Standard deviation	91254605.2
Coefficient of variation (CV)	0.5276010671
Kurtosis	-1.262767386
Mean	172961373.5
Median Absolute Deviation (MAD)	84110000
Skewness	-0.1130137734
Sum	9.443690991 × 10¹⁰
Variance	8.32740297 × 10¹⁵
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
305593498	10	1.8%
154543498	6	1.1%
286933498	5	0.9%
54923498	5	0.9%
66283498	5	0.9%
252753498	4	0.7%
267283498	4	0.7%
249133498	4	0.7%
81753498	4	0.7%
32303498	3	0.5%
Other values (422)	496	90.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
233498	1	0.2%
483498	1	0.2%
563498	1	0.2%
2223498	1	0.2%
2923498	1	0.2%

Value	Count	Frequency (%)
332673498	1	0.2%
324413498	1	0.2%
322403498	1	0.2%
321573498	1	0.2%
321093498	1	0.2%

city_id
Real number (ℝ_≥0)

Distinct	202
Distinct (%)	37.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	46507.63553
Minimum	230
Maximum	99654
Zeros	0
Zeros (%)	0.0%
Memory size	4.4 KiB

Quantile statistics

Minimum	230
5-th percentile	10346
Q1	21710.25
median	46779.5
Q3	65279.75
95-th percentile	90633
Maximum	99654
Range	99424
Interquartile range (IQR)	43569.5

Descriptive statistics

Standard deviation	26134.6373
Coefficient of variation (CV)	0.5619429368
Kurtosis	-1.023818627
Mean	46507.63553
Median Absolute Deviation (MAD)	20386.5
Skewness	0.05573643737
Sum	25393169
Variance	683019266.6
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10346	80	14.7%
80562	27	4.9%
20326	22	4.0%
40441	21	3.8%
50898	15	2.7%
90633	12	2.2%
44366	10	1.8%
60537	9	1.6%
47282	9	1.6%
34348	6	1.1%
Other values (192)	335	61.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
230	1	0.2%
1298	6	1.1%
4334	4	0.7%
4783	1	0.2%
4831	1	0.2%

Value	Count	Frequency (%)
99654	1	0.2%
99315	2	0.4%
97301	2	0.4%
96278	2	0.4%
94700	1	0.2%

payment_id
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

1491	186
1779	181
1619	93
1811	62
1523	24

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	2184
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1491
2nd row	1491
3rd row	1491
4th row	1491
5th row	1491

Value	Count	Frequency (%)
1491	186	34.1%
1779	181	33.2%
1619	93	17.0%
1811	62	11.4%
1523	24	4.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
1491	186	34.1%
1779	181	33.2%
1619	93	17.0%
1811	62	11.4%
1523	24	4.4%

Most occurring characters

Value	Count	Frequency (%)
1	949	43.5%
9	460	21.1%
7	362	16.6%
4	186	8.5%
6	93	4.3%
8	62	2.8%
5	24	1.1%
2	24	1.1%
3	24	1.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2184	100.0%

Most frequent character per category

Value	Count	Frequency (%)
1	949	43.5%
9	460	21.1%
7	362	16.6%
4	186	8.5%
6	93	4.3%
8	62	2.8%
5	24	1.1%
2	24	1.1%
3	24	1.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	2184	100.0%

Most frequent character per script

Value	Count	Frequency (%)
1	949	43.5%
9	460	21.1%
7	362	16.6%
4	186	8.5%
6	93	4.3%
8	62	2.8%
5	24	1.1%
2	24	1.1%
3	24	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2184	100.0%

Most frequent character per block

Value	Count	Frequency (%)
1	949	43.5%
9	460	21.1%
7	362	16.6%
4	186	8.5%
6	93	4.3%
8	62	2.8%
5	24	1.1%
2	24	1.1%
3	24	1.1%

platform_id
Real number (ℝ_≥0)

Distinct	8
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	29870.09158
Minimum	29463
Maximum	30391
Zeros	0
Zeros (%)	0.0%
Memory size	4.4 KiB

Quantile statistics

Minimum	29463
5-th percentile	29463
Q1	29463
median	29815
Q3	30231
95-th percentile	30359
Maximum	30391
Range	928
Interquartile range (IQR)	768

Descriptive statistics

Standard deviation	336.6185586
Coefficient of variation (CV)	0.01126941837
Kurtosis	-1.507933664
Mean	29870.09158
Median Absolute Deviation (MAD)	352
Skewness	0.08296615676
Sum	16309070
Variance	113312.054
Monotocity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
29463	172	31.5%
29815	157	28.8%
30231	148	27.1%
30359	42	7.7%
29751	12	2.2%
30391	10	1.8%
30199	4	0.7%
29495	1	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
29463	172	31.5%
29495	1	0.2%
29751	12	2.2%
29815	157	28.8%
30199	4	0.7%

Value	Count	Frequency (%)
30391	10	1.8%
30359	42	7.7%
30231	148	27.1%
30199	4	0.7%
29815	157	28.8%

transmission_id
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

212	420
4356	59
4228	38
4324	26
4996	3

Length

Max length	4
Median length	3
Mean length	3.230769231
Min length	3

Characters and Unicode

Total characters	1764
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	212
2nd row	212
3rd row	212
4th row	212
5th row	212

Value	Count	Frequency (%)
212	420	76.9%
4356	59	10.8%
4228	38	7.0%
4324	26	4.8%
4996	3	0.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
212	420	76.9%
4356	59	10.8%
4228	38	7.0%
4324	26	4.8%
4996	3	0.5%

Most occurring characters

Value	Count	Frequency (%)
2	942	53.4%
1	420	23.8%
4	152	8.6%
3	85	4.8%
6	62	3.5%
5	59	3.3%
8	38	2.2%
9	6	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1764	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	942	53.4%
1	420	23.8%
4	152	8.6%
3	85	4.8%
6	62	3.5%
5	59	3.3%
8	38	2.2%
9	6	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	1764	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	942	53.4%
1	420	23.8%
4	152	8.6%
3	85	4.8%
6	62	3.5%
5	59	3.3%
8	38	2.2%
9	6	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1764	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	942	53.4%
1	420	23.8%
4	152	8.6%
3	85	4.8%
6	62	3.5%
5	59	3.3%
8	38	2.2%
9	6	0.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	customer_id	order_date	order_hour	customer_order_rank	is_failed	delivery_fee	amount_paid	restaurant_id	city_id	payment_id	platform_id	transmission_id
0	2699	00c9c435cd4a	2017-01-21	18	NaN	1	0.0000	16.8327	30753498	40441	1491	29751	212
1	3667	010a7ac13c41	2016-06-17	16	NaN	1	0.0000	7.9650	123033498	44366	1491	30359	212
2	4197	0132d2b7563c	2016-10-12	12	NaN	1	1.7255	27.3996	154543498	10346	1491	29463	212
3	4835	0173219940e8	2015-09-03	18	NaN	1	0.0000	8.3367	227553498	10346	1491	29463	212
4	6315	01e4f035a965	2017-02-23	20	NaN	1	0.0000	7.8057	37623498	86381	1491	30231	212
5	6754	0204f88cf9eb	2015-10-09	16	NaN	1	0.0000	15.9300	88173498	46276	1619	29815	4356
6	6997	0219915c5588	2015-08-04	20	NaN	1	0.0000	5.7879	125243498	6849	1619	30231	4324
7	7467	024d7e283259	2016-02-20	18	NaN	1	0.0000	9.8235	277163498	53571	1619	30231	4228
8	8915	02d626f7f85b	2015-06-12	21	NaN	1	0.0000	25.9128	218723498	85280	1491	29815	212
9	10057	031c273bc06d	2015-11-23	21	NaN	1	1.7255	10.0359	154543498	10346	1491	29463	212

Last rows

	df_index	customer_id	order_date	order_hour	customer_order_rank	is_failed	delivery_fee	amount_paid	restaurant_id	city_id	payment_id	platform_id	transmission_id
536	779268	fd8df7703a7f	2015-11-10	18	NaN	1	0.00000	11.95281	190433498	44366	1619	29815	4356
537	779610	fdb30c327261	2016-05-11	0	NaN	1	1.47900	9.23940	63883498	58320	1491	30359	212
538	779611	fdb30c327261	2016-05-11	0	NaN	1	1.47900	9.23940	63883498	58320	1491	30359	212
539	781102	fe330d878d70	2016-12-05	12	NaN	1	0.73457	6.83928	135853498	20326	1491	30359	212
540	781450	fe4bd15da855	2016-04-09	19	NaN	1	0.00000	10.30140	6113498	40441	1779	30231	212
541	781461	fe4bd15da855	2016-05-22	15	NaN	1	0.00000	8.01810	6113498	40441	1779	30231	212
542	782393	fe97f3d7093f	2016-09-11	18	NaN	1	0.00000	30.12894	245613498	31813	1491	29463	212
543	782962	fec8c74dc7db	2016-09-27	16	NaN	1	0.00000	9.02700	75243498	69457	1491	29815	212
544	785818	ffbca9c1cc9c	2016-11-18	14	NaN	1	0.00000	10.67310	77013498	50898	1491	29815	212
545	786062	ffcdbbc627fe	2015-09-03	22	NaN	1	0.49300	9.02700	200943498	55797	1491	30231	212

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows